Category: Uncategorized
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Deep learning improves protein binder design tenfold
In recent years, de novo design of high-affinity protein-binding proteins has become a reality, solely based on target structural information. However, there is still significant room for improvement, as the overall design success rate remains low. In this post, we discuss our lab’s latest open-access research paper published in Nature Communications, which explores the augmentation…
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Top-down design of protein architectures with reinforcement learning
Today we report in Science [PDF] the successful application of reinforcement learning to a challenge in protein design. This research is a milestone in the use of artificial intelligence for science, and the potential applications are vast, from developing more effective cancer treatments to new biodegradable textiles. A team led by Isaac Lutz, Shunzhi Wang, PhD, and…
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Design of binders for disordered targets
Today we report in Nature the design of proteins that recognize and bind to the so-called “intrinsically disordered regions” of proteins and peptides. The body produces such disordered molecules naturally, but many have been linked to health disorders, including myeloma and other cancers. “Disordered proteins play important roles in biology. By designing new proteins that…
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RFdiffusion now free and open source
Today we are making RFdiffusion, our artificial intelligence (AI) program that can generate novel proteins with potential applications in medicine, vaccines, and advanced materials, free for both non-profit and for-profit use under a governed license. The software, which has been tested in the lab, is much faster and more capable than prior protein design tools.…
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De novo design of small beta barrel proteins
The de novo design of small proteins with beta-barrel topologies has been a challenge for computational design due to the complexity inherent in these folds. In a new study appearing in PNAS, a team led by Baker Lab research scientist David E. Kim describes the successful design and characterization of four different classes of small…
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Machine learning generates custom enzymes
Today we report in Nature [PDF] the computational design of highly efficient enzymes unlike any found in nature. Laboratory testing confirms that the new light-emitting enzymes, called luciferases, can recognize specific chemical substrates and catalyze the emission of photons very efficiently. This is an important step in the field of protein design as enzymes have many uses…
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NBC: “Scientists use new A.I. tech to fight diseases”
NBC News Now recently covered how we are using artificial intelligence to accelerate protein science. From NBC News Now A group of researchers at the University of Washington is harnessing artificial intelligence to improve how scientists develop proteins for medicines and vaccines. NBC’s Dr. Akshay Syal has a closer look at the potential medical breakthrough.
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New York Times: “A.I. Turns Its Artistry to Creating New Human Proteins”
The New York Times recently wrote about one of our latest preprints. In it, we introduce a generative diffusion model for protein design called RFdiffusion. [Update: This research was subsequently published in Nature, and RFdiffusion is now free and open source.] From the New York Times: Last spring, an artificial intelligence lab called OpenAI unveiled…